Introduction

The deer tick or blacklegged tick (Ixodes scapularis) is the most medically relevant species of hard tick that in New York State (NYS). I. scapularis populations in NYS may carry a plethora of pathogens, including but not limited to:

  • Borrelia burgdorferi - the causitive agent of Lyme disease
  • Anaplasma phagocytophilum - the causitive agent of human granulocytic anaplasmosis
  • Babesia microti - the causitive agent of babesiosis in humans
  • Borrelia miyamotoi - causative of a relapsing tick fever

The prevalence of the above pathogens varies both spatially and temporally in NYS, which results in varying risk for NYS citizens. Because these pathogens are not transmitted from tick to tick transovarially, they are required to be maintained throughout populations of animal hosts in the various ecosystems of NYS. Data suggests that certain land use and land cover types are beneficial for populations of animals which maintain these pathogens, and potentially for the pathogen’s themselves. This project aims to explore any trends between pathogen prevalence within I. scapularis at the county level and land use / land cover types in NYS.

Materials and methods

[~ 200 words]

Narrative: Clear narrative description of the data sources and methods. Includes data from at least two sources that were integrated / merged in R.

Code: The code associated with the project is well organized and easy to follow. Demonstrates mastery of R graphics and functions.

Data: The underlying data are publicly accessible via the web and downloaded/accessed within the Rmd script. If you want to use your own data, you must make it available on a website (e.g. Figshare) so that others are able to re-run your code.

You can do bullets like this:

  • The first most important thing
  • The second most important thing
  • The third most important thing

You can do numbers like this:

  1. The first most important thing
  2. The second most important thing
  3. The third most important thing

Packages required are below:

library(readr)
library(tidyverse)
library(FedData)
library(raster)
library(sf)
library(spData)
library(leaflet)
library(purrr)
library(MODIS)
library(MODISTools)
library(gdalUtilities)
library(gdalUtils)
library(rgdal)
library(tmap)
library(glue)

Download and clean all required data

tdir=tempdir()
## Tick data
adulturl <- "https://health.data.ny.gov/api/views/vzbp-i2d4/rows.csv?accessType=DOWNLOAD&bom=true&query=select+*"
nymphurl <- "https://health.data.ny.gov/api/views/kibp-u2ip/rows.csv?accessType=DOWNLOAD&bom=true&query=select+*"
if(file.exists(paste(tdir,"/Adultdata.csv",sep=""))==FALSE){
download.file(adulturl, destfile = file.path(tdir,"/Adultdata.csv"))}
if(file.exists(paste(tdir,"/Nymphdata.csv",sep=""))==FALSE){
download.file(nymphurl,destfile = file.path(tdir,"/Nymphdata.csv"))}
Nymphdata <- read_csv(paste(tdir,"/Nymphdata.csv",sep=""))
Adultdata <- read_csv(paste(tdir,"/Adultdata.csv",sep=""))
shpurl="http://gis.ny.gov/gisdata/fileserver/?DSID=927&file=NYS_Civil_Boundaries.shp.zip"
if(file.exists(paste(tdir,"/NYS_Civil_Boundaries_SHP/Counties_Shoreline.shp",sep=""))==FALSE){
download.file(shpurl, destfile = file.path(tdir,"Boundaries.zip"))
unzip(file.path(tdir,"Boundaries.zip"),exdir = tdir)
Cnt=read_sf(paste(tdir,"/NYS_Civil_Boundaries_SHP/Counties_Shoreline.shp",sep=""))}
#list.files(paste(tdir,"/NYS_Civil_Boundaries_SHP",sep=""))
County_Boundaries = Cnt[,c(1,18)]
NYS = st_union(County_Boundaries)
simpSpNYS=st_simplify(NYS,
                      dTolerance=100)
SpNYS=as(NYS,Class="Spatial")
## `summarise()` regrouping output by 'Year' (override with `.groups` argument)
## `summarise()` regrouping output by 'Year' (override with `.groups` argument)
## New names:
## * Year -> Year...1
## * Pathogen -> Pathogen...2
## * Year -> Year...4
## * Pathogen -> Pathogen...5
## `summarise()` regrouping output by 'Year' (override with `.groups` argument)
## `summarise()` regrouping output by 'Year' (override with `.groups` argument)
## New names:
## * Year -> Year...1
## * Pathogen -> Pathogen...2
## * Year -> Year...4
## * Pathogen -> Pathogen...5

Add any additional processing steps here.

Results

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Conclusions

[~200 words]

Clear summary adequately describing the results and putting them in context. Discussion of further questions and ways to continue investigation.

References

All sources are cited in a consistent manner